Let’s be real; no one wants to talk to a one-size-fits-all chatbot 😒

In the early days of the chatbot, we were all treated to the concept of a generic one-size-fits-all chatbot, and oh what a treat that was. It was a pleasant surprise if the chatbot could even refer to the user by their name let alone leverage any meaningful data on the user.

In the end, we all became frustrated by drawn-out chatbot conversations that ultimately provided little value, and thus our pessimism towards the chatbot industry grew. As a result, today’s chatbots need to prove to users that they’re more than their embarrassing predecessors to garner worthwhile chatbot user engagement numbers.

Step 1: ‘Wow’ users by knowing the meaningless details 😲

This is definitely the low hanging fruit in this formula and something everyone should leverage to help with chatbot user engagement. Many users will approach a new chatbot conversation with a heavy dose of trepidation and pessimism; therefore the chatbot’s welcome message is the perfect opportunity to show that your chatbot has some intelligence.

Greeting the user by their name, mentioning the weather where they live, changing the salutation based on the time of day (good morning, good afternoon, good evening), and displaying multiple variations of the chatbot’s welcome message to help shake things up for repeat users are a great start to improving chatbot user engagement with personalization.

The key here is to show users that they’re not interacting with one of those pesky one-size-fits-all chatbots without having to do too much heavy lifting in regards to what’s under the chatbot’s hood. You need to get the user to overcome any negative connations they have about chatbots and commit to giving your chatbot a shot by responding and engaging it in a conversation.

Step 2: Leverage historical user data to cut out the unnecessary chit-chat ✂️

Any data you have regarding users’ past interactions with your chatbot or the product it supports are perfect fodder for creating a personalized user experience that moves the needle when it comes to chatbot user engagement. This can be as simple as a chatbot that helps users order pizza remembering a user’s last order and their delivery address.

You’ll often hear people say that past behavior is the best predictor of future behavior and that concept resonates when it comes to chatbot conversations. For example, in the case of the pizza-ordering chatbot, if a user has placed the same order three out of the last four times then the chatbot can save the user a lot of time and typing by asking if they’d like to place that order again upfront. This provides value to the user and will help improve chatbot user engagement.

The main takeaway here is that a chatbot should not treat repeat users the same as a first-time user. Would you want your fifth conversation with a new acquaintance to feel exactly the same as the initial one? We experience the benefits of conversational context in our everyday conversations with other humans. It’s time for chatbots to get on the same level.

Step 3: Use ‘live’ user activity to provide the ultimate chatbot personalization experience 😍

This is by far the most powerful form of chatbot personalization covered in this article and a ‘must’ when it comes to chatbot user engagement for any chatbots tailored for sales or support. The premise is that the chatbot conversation is customized based on how the user is engaging with the chatbot or the product it supports in real-time.

For example, a chatbot that knows where a particular user is in the product it supports could ask the user if they’re encountering the issue most commonly associated with that specific part of the product. Another great example is a sales-focused chatbot that provides product recommendations based on what the user is shopping for in their current session. If I’m shopping for shoes, the chatbot better not provide me with product recommendations for hats.

While reaching this state of chatbot personalization is no easy undertaking, the positive impact it can have on chatbot user engagement cannot be overstated. Real-time personalization like this provides tremendous value that will help impress the most demanding users and keep them coming back for more.

So what are you waiting for? Amaze your chatbot’s users by making them feel as though the conversation is personalized to them, and watch your chatbot user engagement metrics soar as a result.

3 Steps to Grow Chatbot User Engagement w/ Personalization was originally published in UX Planet on Medium, where people are continuing the conversation by highlighting and responding to this story.

Disclaimer: This strategy isn’t for the faint of heart… 😲

If you’re looking for basic beginner-level chatbot UX design strategies, then I recommend you check out this article I wrote in 2018 on the ‘6 Chatbot UX Design ‘Must-haves’ for 2018.’ This piece you’re reading is an expansion on the chatbot UX design principles I covered last year and is for those looking to get their feet wet in advanced chatbot UX design concepts.

In 2019 it’s all about the chatbot personalization ✏️

Have you ever encountered a chatbot without personalization in the wild? If you have, I’m sure you’ll agree with me when I say that it’s truly a brutal user experience. It feels like a visual cloud-based presentation of those phone IVR queues that we’ve all grown to despise.

Chatbots without conversational personalization put users through a one-size-fits-all conversation path that generally requires users to select preset response options (usually via buttons) over and over again until they maybe… just maybe… find what they’re looking for.

It sounds frightening from a user perspective, doesn’t it? Well, it is. Trust me…

If you want a successful chatbot UX design strategy that promotes user engagement and provides value to the chatbot’s users then you need to make each individual user feel as though the conversation is tailored to their needs and situation. Addressing the user by their name and customizing the salutation based on the time of day (good morning, good afternoon, good evening, etc.) is not going to cut it 2019.

While the aforementioned personalization examples should still be included in your chatbot UX design strategy for 2019, there are more advanced levels of personalization that will contribute much more to a chatbot’s success.

Leverage users’ conversation history to cut the unnecessary chit-chat ✂️

This idea is vital to the chatbot UX design strategy of chatbots in the service sector. The concept is simple. Use what you already know about the user from their previous interactions with the chatbot or the product it supports, to create an optimized conversation flow that minimizes the user’s path to their desired solution.

For example, if your chatbot allows users to order pizza then start off by authenticating the identity of the user, figure out whether they’re an existing customer, and if they’re a repeat customer then take advantage of what you already know. This can involve tailoring order recommendations based on past order history, remembering users’ delivery addresses and payment methods, and much more.

Not only will this chatbot UX design strategy help more users reach their desired state, which in this case is a hot pizza at their doorsteps ASAP, but it will provide a smoother, more intuitive conversation path that cuts down on the annoyingly unnecessary chit-chat such as asking the user for their delivery address. If this is my fifth time ordering pizza with this chatbot then it better remember my address and at the most just ask me to confirm it.

The applications for this particular chatbot UX design strategy are endless, however, it can sometimes be easier said than done to actually deliver on it. None the less, big results require a big effort. You’ve got this!

For truly mind-blowing results, personalize the conversation based on real-time user activity 🥇

If you really want to create a chatbot that impresses users then add this nugget to your chatbot UX design strategy for 2019. This is about as good as it gets when it comes to making users feel as though the conversation is tailored to them.

This chatbot UX design concept is particularly powerful for chatbots aimed at providing sales or customer support. The idea is simple in theory. Customize the conversation design based on the real-time activity of that user with the chatbot and the website or product it supports. Unfortunately, the implementation is likely not going to be simple…

A great example of this particular chatbot UX design strategy in practice is a support-based chatbot that is able to tailor its conversation based on the current activity of that user in the product it supports. If you know what section of the product the user is in and have data that indicates a high probability of them having a particular issue, then ask that user if that is in fact the problem they’re experiencing.

Another prime use case for this chatbot UX design strategy involves a sales-based chatbot that provides customized product recommendations in the conversation based on what the user is currently shopping for. If I’m shopping for hats and I start a conversation with this chatbot, it better not start off by recommending pairs of jeans.

While this chatbot UX design concept is a difficult one to implement, the fruits of your efforts will be well worth it. Not only does this score exceptionally high on the ‘wow-factor’ scale, but it provides genuine value to users that they likely won’t get through alternative means. That’s how you design a winning chatbot.

Keep calm and chatbot on… 🤖

If your chatbot isn’t at this level yet don’t fret. As I already mentioned, this chatbot UX design strategy is definitely on the more advanced end of the spectrum.

Do the best you can at present, but keep in mind that the chatbot space is moving in this direction and you’ll need to get here at some point. If you don’t, it shouldn’t be much of a shock when your once-promising chatbot becomes as extinct as the dinosaurs.

Cheers to a successful 2019!

The Ultimate Chatbot UX Design Strategy for 2019 was originally published in Chatbots Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.

Users will misuse your chatbot far more often than you expect 🤖

If you think most users will use your chatbot as expected this is clearly your first rodeo. Not only will user conversations surprise you but you will likely find yourself dumbfounded by many of them.

To expect a chatbot conversation to go as planned is the literal equivalent to meeting a stranger and expecting to know exactly how that conversation will unfold ahead of time. Plain and simple, it’s nearly impossible to predict chatbot user behavior.

Moral of the story here is to expect the unexpected and take whatever measures you can to safeguard your precious chatbot from user error as best as you can. Otherwise, don’t be surprised when your chatbot fails miserably.

If you think users read everything your chatbot says, you’re wrong 🤦

This one of the first and harshest lessons I learned after building my first chatbot. Unless your chatbot is designed purely for entertainment purposes — in which case this may still happen — expect users to frequently skim through your chatbot’s responses instead of reading them verbatim.

Users are ultimately looking to get some sort of value from your chatbot, and if that value isn’t pure entertainment, then they will try to get through the chatbot conversation as quickly as possible to reach the prize aka that value they’re seeking. This cruel reality only increases the likelihood that users will make mistakes when navigating through your chatbot’s conversation flow.

The key takeaway here is that you need to keep your chatbot responses brief and straight to the point wherever possible. Any unnecessary dialogue that doesn’t help the user navigate to what they’re looking for is just adding to the probability of user error and misuse.

Using Single-word chatbot buttons such as ‘Yes’ or ‘No’ is like begging for user error 🙏

Now that we’ve established the likelihood that users will skim through and misread your chatbot content, let’s couple that with the use of vague, single-word chatbot buttons such as ‘Yes’ or ‘No’. I’m going to provide a simple real-world example that actually occurred in a chatbot that I previously built to prove why these minuscule chatbot buttons are so dangerous.

In this example, we have a support-based chatbot whose initial message to the user asks them to confirm whether or not they’re an existing customer. This is a critical inquiry as existing customers should continue through the chatbot conversation and hopefully get the support they need from the chatbot. Users that are new customers need to get routed to a contact center queue where a sales rep will reach out to them.

Users that are not paying attention to the content in this initial message may click the ‘Yes’ chatbot button indicating that they’re an existing customer where in fact they may have just made a mistake. Now, this user is getting free support instead of a callback from a sales rep. This is a simple example, but you can see just how costly user mistakes like this can be to your chatbot’s success.

Opt for brevity except when labeling your chatbot buttons ✏️

In that example, the ‘Yes’ and ‘No’ chatbot buttons should’ve been labeled ‘Yes, I’m an existing customer’ and ‘No, I’m new’ to help prevent user error. While users will often skim through a chatbot response, they’re generally far more likely to pay attention to the label of a chatbot button since they have to focus on the chatbot button while engaging in the act of clicking on it.

So, when building your next chatbot opt for brevity in your chatbot messages to minimize the likelihood of users skimming, but make sure to label chatbot buttons in a manner that makes it clear what action the user will be taking by clicking on it even if they didn’t read a word of the associated chatbot message.

As always, remember to ‘Keep calm and chatbot on’…

This story is published in The Startup, Medium’s largest entrepreneurship publication followed by +388,456 people.

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Why You Should NEVER Use ‘Yes’ or ‘No’ Chatbot Buttons was originally published in The Startup on Medium, where people are continuing the conversation by highlighting and responding to this story.

You expected chatbot user adoption to be easy, didn’t you? 😂

Let’s be honest. When building your chatbot, you were so thrilled with the user experience that you expected users to flock to it in droves once it went live. Now you’re three months in post-live and practically banging your head against the wall when analyzing the user data.

Not only are users not lining up to use your chatbot as you’d hoped, but the numbers are well below the benchmarks you’ve set. Don’t worry; you’re not alone. Several inherent obstacles are a hindrance to virtually all chatbot user adoption, but they can be overcome. Obligatory disclaimer: it won’t be easy though…

1. Chatbots are unproven versus the status quo 🤔

Remember the struggle mobile apps had converting web browser users several years ago? That same struggle seems pretty non-existent today, doesn’t it?

Chatbots are currently in the same situation that mobile apps were in several years ago. Users are often creatures of habit and will get comfortable with the workflows and technologies that they use on a day-to-day basis. Getting users to cross the line and adopt something new is no easy feat, and the same applies to chatbot user adoption.

So what can you do to overcome this?

First off, be patient and persistent with a focus on the long term. If you analyze your chatbot’s user adoption in the short term, you will find yourself overreacting and making impulse decisions that don’t fit with your best long-term interests.

In addition to being patient, you need to make sure your chatbot leaves an excellent initial impression and showcases some form of value to the user that the status quo isn’t providing. If users don’t see this value almost immediately or see a product riddled with bugs and shortcomings, you can bet that they will immediately crawl back to whatever product or tool they were using before they gave your chatbot a shot.

2. User expectations often far exceed reality 🤖

This struggle is all too real in the chatbot space right now. So many users expect chatbots and the AI that powers them to be something out of a Sci-Fi movie. Unfortunately, that’s just not the reality in today’s chatbot landscape.

While chatbots can do a lot of great things and provide excellent opportunities for automation, they are still not smarter than humans. The chatbot user adoption struggle is real folks…

So what can you do to overcome this?

Don’t oversell your chatbot as something it isn’t. If your chatbot can only answer basic questions about the weather, that’s fine, but don’t sell users on it being their a personal meteorologist in their pocket. If you do that, you can expect a lot of first-time users that will never become recurring users.

Crafting a sound welcome message for your chatbot can set realistic expectations for users regarding what it can and can not do. While this may be a less sexy way to sell your chatbot, it will improve the overall user experience and lead to more repeat usage.

3. Organizational Failure to Properly Integrate Chatbots 🤦

This struggle applies to organizations trying to implement chatbots into their existing technology portfolio and everyday workflows. Too often, there is a failure to truly understand the potential impact chatbots will have when thrown into an organization for internal use.

I get it. Chatbots are sexy and one of the most prominent technological fads at the moment, but that doesn’t mean they’re miracle workers and always the right decision. There are instances where chatbots may not coexist well with the workflows or existing technologies within an organization, and that’s fine. Forcing chatbots into the mix just for the sake of having chatbots, however, is not a good practice.

So what can you do to overcome this?

Whether you work for an external agency looking to integrate chatbots within a client organization or a key stakeholder vetting the possibility of incorporating chatbots internally, you need to do your due diligence and have a success plan in place. Key things to consider include:

• Do chatbots create synergy with the rest of the organization’s technologies?
• Will chatbots make a noticeable difference in the productivity and success of the organization, and if so, what metrics and goals can be used to assess their effectiveness?
• Does the organization have a culture that will embrace the use of chatbots?
• What is the potential ROI for the adoption of chatbots and how likely is it that this ROI can be met?

If any of those questions result in a resounding ‘No,’ then you may want to reconsider the chatbot implementation or at the very least create a plan that helps to flip that resounding ‘No’ into a potential ‘Yes.’

4. User activity is completely unpredictable 🙃

This struggle is arguably the most frustrating and challenging when it comes to chatbot user adoption yet also the most enjoyable aspect of working on chatbots at times. This struggle of never knowing exactly how users are going to interact with a chatbot is part of the thrill that makes chatbots so fun to build and chatbot user adoption so tricky.

Let’s face it, you can add beautiful menus of response buttons and as many utterances to those intents as you want, but ultimately users are going to create a conversation that you and your chatbot are entirely unprepared for. It’s inevitable but ultimately part of the fun. Embrace the uncertainty, move quickly, and learn from your mistakes.

So what can you do to overcome this?

Analytics, analytics, and oh yeah, more analytics! Analytics are critical to identifying the biggest pitfalls that are hindering chatbot user adoption. Without analytics, you will find yourself blindly making decisions and overreacting to short-term trends.

You’re never going to build a chatbot that will appease every user it encounters so you need to leverage analytics to figure out how to design your chatbot in a way that pleases the masses while pissing off the fewest. Oh, and when your chatbot does fail to satisfy what a user wants, make sure to have an effective fallback response that at least attempts to get the user back on track in the conversation.

5. Public fear and distrust over Chatbots and AI 😨

Unfortunately, this obstacle is out of your control for the most part. For many, AI and chatbots represent a brewing evil that is out to take our jobs and eventually take over planet earth. While the rest of us all know that couldn’t be further from the truth, this public perception that has been building over the last few years can negatively impact chatbot user adoption.

So what can you do to overcome this?

As I already mentioned, there is unfortunately only so much you can do to overcome this chatbot user adoption struggle. Branding your chatbot as a tool that provides positive value to humanity is a start and can be further aided by giving your chatbot a friendly avatar and personality.

Remember that over time this negative connotation will die down as the public sees for themselves that AI and chatbots are not the root of all evil and in reality benefiting humanity.

You can do it. No seriously, you really can 💪

Be patient, learn from your mistakes, and don’t give up. If you do this you will get over your chatbot user adoption struggles with time. After all, nothing worth accomplishing ever comes easy.

Keep calm and chatbot on…

5 Obstacles to Chatbot User Adoption & How to Overcome Them was originally published in Chatbots Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.

One of the most significant challenges for those trying to offer service and support is being able to relay the proper internal knowledge to customers who need it promptly. As organizations and their product and service offerings grow, the amount of support-related information continuously expands. As this scope of knowledge and information broadens the gap between a tenured, experienced support agent and a new hire grows tremendously.

AI-powered automation can help bridge this gap and make all of your organization’s support and service-related knowledge accessible to your customers at the click of a button. We created the Relay Knowledge Ecosystem to provide the knowledge organization and automation needed to take your support or service offering to the next level.

What is the Relay Knowledge Ecosystem?

The Relay Knowledge Ecosystem brings your organization’s knowledge to your customers through chatbots and knowledge base articles that are fueled by Artificial Intelligence (AI). Getting onboard and using the Relay Knowledge Ecosystem is a breeze too as in many cases we can import your organization’s existing knowledge base (if you have one) and make it immediately accessible via chatbots and a visual search bar embedded on a landing page with customizable branding.

Don’t worry about building bots. We’ve fully automated that process with the Relay software. Now your organization can merely focus on creating a vast knowledge base while knowing that it will be accessible via chatbots and a search bar presentation similar to the Google experience we all know and love. Talk about killing two birds with one stone…

The Relay Knowledge Base & Search Bar. Your organization’s personal Google engine

When it comes to searching and accessing internal knowledge, it’s tough to beat the concept of a Google-esque search bar. Unlike a chatbot, a search engine is tailored to display a bevy of relevant search results thus increasing the likelihood that you find exactly what you’re looking for.

While chatbots are an ideal solution for displaying knowledge to external customers, your organization’s internal employees may prefer to find and access knowledge via a search bar since they will likely have the insight needed to weed through a selection of search results. Your customers probably won’t have that same insight, and therefore a conversational approach via chatbots is more likely to provide success.

Deliver your knowledge to your customers via Chatbots

While a traditional search bar approach works great for your internal team, it often requires context and insights for success that your customers don’t have. When delivering your organization’s knowledge to customers, chatbots are the way to go.

The Relay platform uses proprietary AI and Machine Learning (ML) powered search algorithms that can deliver the same piece of content to your internal team via the Google-like search bar we just highlighted and/or your external customers via the Relay Bots. Just create your piece of knowledge content once, and decide whether it’s searchable via the search bar, chatbots, or both. With the Relay Knowledge Ecosystems, we’re already making manual chatbot creation a thing of the past.

So what’s next?

If you aren’t currently using knowledge bases and chatbots towards the goal of being able to provide better service and support, then you’re running the risk of falling well behind the competition. Start doing your research and find out whether or not a chatbot and/or knowledge base aligns with the focus of you or your organization. For tips on determining the best chatbot platform for your needs check out one of our previous posts on the subject.

We would love to give you a demo to show you just how powerful our native chatbots are when combined with the Relay intelligent support platform. Schedule a demo, and we’ll help you transform your support and service operations and take your organization to new heights.

Originally published at thinkrelay.com on August 20, 2018.

Introducing the Relay Knowledge Ecosystem was originally published in Support Automation Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.